Create README.md
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README.md
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---
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language:
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- sah
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license: apache-2.0
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tags:
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- automatic-speech-recognition
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- mozilla-foundation/common_voice_8_0
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- generated_from_trainer
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- sah
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- robust-speech-event
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- model_for_talk
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datasets:
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- mozilla-foundation/common_voice_8_0
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model-index:
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- name: sammy786/wav2vec2-xlsr-sakha
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Common Voice 8
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type: mozilla-foundation/common_voice_8_0
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args: sah
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metrics:
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- name: Test WER
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type: wer
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value: 36.15
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- name: Test CER
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type: cer
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value: 8.06
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---
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# sammy786/wav2vec2-xlsr-sakha
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - sah dataset.
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It achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):
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- Loss: 21.39
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- Wer: 30.99
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## Model description
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"facebook/wav2vec2-xls-r-1b" was finetuned.
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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Training data -
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Common voice Finnish train.tsv, dev.tsv and other.tsv
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## Training procedure
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For creating the train dataset, all possible datasets were appended and 90-10 split was used.
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.000045637994662983496
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 13
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine_with_restarts
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 15
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- mixed_precision_training: Native AMP
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### Training results
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| Step | Training Loss | Validation Loss | Wer |
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|------|---------------|-----------------|----------|
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| 200 | 4.541600 | 1.044711 | 0.926395 |
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| 400 | 1.013700 | 0.290368 | 0.401758 |
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| 600 | 0.645000 | 0.232261 | 0.346555 |
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| 800 | 0.467800 | 0.214120 | 0.318340 |
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| 1000 | 0.502300 | 0.213995 | 0.309957 |
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### Framework versions
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- Transformers 4.16.0.dev0
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- Pytorch 1.10.0+cu102
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- Datasets 1.17.1.dev0
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- Tokenizers 0.10.3
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#### Evaluation Commands
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1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test`
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```bash
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python eval.py --model_id sammy786/wav2vec2-xlsr-sakha --dataset mozilla-foundation/common_voice_8_0 --config sah --split test
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```
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